Cassandra is a distributed and scalable database management system used for real-time data processing.
It is highly valued for its ability to handle large amounts of data, scalability, high availability, fault tolerance, and flexible data model.
It is commonly used in finance, e-commerce, and social media industries.
InfluxDB is open-source software that helps developers and enterprises alike to collect, store, process, and visualize time series data and to build next-generation applications. InfluxDB provides monitoring and insight on IoT, application, system, container, and infrastructure quickly and easily without complexities or compromises in scale, speed, or productivity.
InfluxDB has become a popular insight system for unified metrics and events enabling the most demanding SLAs. InfluxDB is used in just about every type of industry across a wide range of use cases, including network monitoring, IoT monitoring, industrial IoT, and infrastructure and application monitoring.
InfluxDB offers its users:
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Infrastructure and application monitoring: Collect, process, and analyze real-time data from edge devices to help optimize distributed infrastructure.
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IoT monitoring and analytics: InfluxDB is designed to store large volumes of time series data and quickly perform real-time analysis on that data. Gain insights from all the sensor data and use the collected data to create and perform automated tasks.
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Network monitoring: Manage responsive and high-performing networks with widely distributed resources.
InfluxDB Benefits
There are several benefits to using InfluxDB . Some of the biggest advantages the solution offers include:
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APIs and ready toolset: InfluxDB can be accessed via a set of powerful tools enabling users to get started quickly, with less programming required. This includes a REST API, extensive client libraries, a wide variety of open-source integrations, and Flux - a functional data scripting language for querying, analysis, and events. The InfluxDB API can be used to write data from edge devices to the InfluxDB instance
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Time series engine: Get any data - events, logs, traces - from any edge device - systems, sensors, queues, databases, and networks. This data is stored in a powerful and high-performing engine capable of ingesting millions of data points per second.
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Community: InfluxDB has a large community of cloud and open-source developers ready to assist users.
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Ready-made templates: Use InfluxDB Templates, a set of tools with a packager and other ready monitoring solutions. These tools allow users to share their monitoring expertise with coworkers and other community members around the world. The Templates gallery offers available templates for some of the most popular tools and applications.
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Enhanced UI: InfluxDB’s UI includes an explorer, dashboarding tools, and a script editor. Use it to easily browse the collected metric and event data and apply common transformations. The dashboarding tool comes with a variety of visualization options that help users view insights from the data. The script editor assists users to quickly master Flux with easily accessible examples, auto-completion, and real-time syntax checking.
Reviews from Real Users
InfluxDB stands out among its competitors for a number of reasons. Two major ones are its flexible integration options and its data aggregation feature.
Shalauddin Ahamad S., a software engineer at a tech services company, notes, “The most valuable features are aggregating the data and the integration with Grafana for monitoring.”
Neo4j is the graph database solution allowing the analysis of complex relationships and patterns in data, leading to better decision-making and improved business processes. The graph database offers easy data integration from multiple sources, providing a more comprehensive view.
The most valuable aspect of a graph database is its performance and response time, as it does not use the join function and only has nodes and raw data. Overall, Neo4j, as a global first-ranking solution, has helped organizations become more efficient and effective in data analysis and decision-making processes.
